code: def get_frequency_aware_conv2d(
      data_format="default",
      freq_aware_name="frequency_aware_conv2d",
      *args,
      **kwargs,
  ):
      """Returns a frequency-aware conv2d layer.
  
      Args:
          data_format (str): specifies the data format of batch input/output.
          freq_aware_name (str): name of the returned layer
          *args: position args for `keras.layers.Conv2D`.
          **kwargs: keyword args for `keras.layers.Conv2D`.
  
      Returns:
          A sequential model of ConcatenateFrequencyMap and Conv2D.
  
      References:
          Koutini, K., Eghbal-zadeh, H., & Widmer, G. (2019).
          `Receptive-Field-Regularized CNN Variants for Acoustic Scene Classification <https://arxiv.org/abs/1909.02859>`_.
          In Proceedings of the Detection and Classification of Acoustic Scenes and Events 2019 Workshop (DCASE2019).
  
      """
      if ("groups" in kwargs and kwargs.get("groups") > 1) or (
          len(args) >= 7 and args[7] > 1
      ):
          raise ValueError(
              "Group convolution is not supported with frequency_aware layer because only the last group"
              "would be frequency-aware, which might not be expected."
          )
  
      freq_map_concat_layer = ConcatenateFrequencyMap(
          data_format=data_format
      )
  
      if data_format != _CH_DEFAULT_STR:
          kwargs["data_format"] = data_format
  
      conv2d = keras.layers.Conv2D(*args, **kwargs)
      return Sequential(
          [freq_map_concat_layer, conv2d], name=freq_aware_name
      )
  
file_path: kapre/kapre/composed.py
imports: from tensorflow import keras
  from tensorflow.keras import Sequential, Model
  from .time_frequency import STFT, InverseSTFT, Magnitude, Phase, MagnitudeToDecibel, ApplyFilterbank, ConcatenateFrequencyMap
  from .None import backend
  from .backend import _CH_FIRST_STR, _CH_LAST_STR, _CH_DEFAULT_STR
label_desc: Use image node_id 6 for calling a global function with example usage: get_frequency_aware_conv2d(data_format, freq_aware_name) and returns: Sequential